Canvas version of this gif from FLRN GIF :
Optimisable, by caching the square roots for example.
#md | DCGAN Generator | |
#mdi | https://miro.medium.com/max/1400/1*5ALjnfAqwcWbOsledTBXsw.png | |
class generator(nn.Module): | |
# initializers | |
def __init__(self, d=128): | |
super(generator, self).__init__() | |
self.deconv1 = nn.ConvTranspose2d(100, d*8, 4, 1, 0) #md | Deconvolution | sub | |
self.deconv1_bn = nn.BatchNorm2d(d*8) #md | Batch Normalization | sub | |
self.deconv2 = nn.ConvTranspose2d(d*8, d*4, 4, 2, 1) | |
self.deconv2_bn = nn.BatchNorm2d(d*4) |
#md | Quadratic Functions | |
#mdi | https://i.ytimg.com/vi/PpwEsHKwmbs/maxresdefault.jpg | |
x = list(range(-10, 10)) | |
quadratic = x**2 | |
#md | Cubic Functions | |
cubic = x**3 |
import requests | |
from bs4 import BeautifulSoup | |
from PyPDF2 import PdfFileMerger, PdfFileReader | |
from io import BytesIO | |
#Parse page with beautiful soup | |
origin = 'https://web.stanford.edu/class/cs224n/readings/' | |
page = requests.get(origin) | |
content = BeautifulSoup(page.text) |
%matplotlib inline | |
from matplotlib import pyplot as plt | |
import numpy as np | |
import pandas as pd | |
plt.style.use('fivethirtyeight') | |
x = np.linspace(0, 10) |
1.Go to the forked cd_to github repository and download the latest release.(zipped) Download From Github.
2.Within cd_to, open the Hyper folder and drag the cd_to.app file into your Applications folder .
3.Now open up Automator and create a new service.
File>New>Service(gear icon).Be sure to save the service with an effective name like "Hyper Terminal at Folder"
def fizzBuzz(amt): | |
for i in xrange(1,amt): | |
if i % 3 == 0 and i % 5 == 0: | |
print "fizzbuzz" | |
elif i % 3 is 0: | |
print "fizz" | |
elif i % 5 is 0: | |
print "buzz" | |
else: | |
print i |
from imdb import IMDb | |
import json | |
i = IMDb() | |
him = i.get_movie('0835010') | |
i.update(him,'episodes') | |
him_items = [] |